Practical Artificial Intelligence for businesses that want answers, not buzzwords

We build models that sit inside your existing workflows, trained on your data, measured against your revenue targets. Based in Scotland, serving the UK and beyond.

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Data scientists working on Artificial Intelligence models in a modern Scottish office
127models deployed
98.4%average uptime
6 weeksmedian time to first prediction
34industries served

Services shaped around the problem, not the technology

Predictive analytics

Demand forecasting, churn prediction, maintenance scheduling. We train regression and classification models on your historical records and hand you a dashboard your operations team can actually use. Most clients see measurable ROI within the first quarter.

Natural language processing

Sentiment analysis on customer reviews. Automated document classification for legal or compliance teams. Chatbot backends that understand context, not just keywords. We fine-tune large language models so they speak your domain vocabulary fluently.

Computer vision

Quality control on production lines, shelf-stock monitoring in retail, medical image screening. Our convolutional neural networks process images in real time at the edge or in the cloud, depending on latency requirements and budget.

AI strategy consulting

Not every problem needs a neural network. Sometimes a well-designed rule engine or a simple logistic regression outperforms a transformer. We audit your data estate, identify the highest-value use cases, and map a twelve-month roadmap with clear milestones and cost estimates.

Data engineering and pipelines

A model is only as reliable as the data feeding it. We design extraction, transformation and loading pipelines that clean, validate and version your datasets. Whether you run on AWS, Azure, GCP or on-premises servers, we integrate with your existing stack.

AI analytics dashboard showing real-time predictions

What changes after deployment

We track every model against the KPIs agreed during scoping. Here are patterns we see across engagements:

  • Inventory waste reduced by 18 to 32 percent for mid-size retailers using our demand forecasting pipeline.
  • Customer support ticket resolution time cut from 14 minutes to under 4 minutes with NLP-powered triage.
  • False-positive rates on fraud detection dropped below 0.6 percent for a Scottish fintech client within eight weeks of go-live.
  • Manufacturing defect detection accuracy reached 99.2 percent on a production line processing 800 units per hour.

From first conversation to production model in four stages

Discovery

We spend two to three days with your team, reviewing data sources, interviewing stakeholders, and defining success criteria. No code written yet, just sharp questions and honest answers about what is feasible.

Proof of concept

A working prototype trained on a subset of your data, delivered within three weeks. You evaluate accuracy, speed, and usability before committing to a full build. If the numbers disappoint, we stop here and you owe nothing beyond the discovery fee.

Production build

Model hardening, API integration, monitoring dashboards, and automated retraining schedules. We deploy into your environment and run load tests until performance meets the SLA.

Ongoing support

Data drift detection, model versioning, quarterly performance reviews. Your account lead is a senior engineer who knows your codebase, not a rotating support desk.

Things clients ask before signing

How much data do we need before AI is worth trying?

It depends on the problem. A classification task with ten clearly defined categories can work well with a few thousand labelled examples. Time-series forecasting usually needs at least two full seasonal cycles. During discovery we assess your data volume and quality honestly. If there is not enough signal, we tell you before any modelling begins.

Do you work with companies outside Scotland?

Yes. Our office is in St. Wintheiser, but most engagements are remote-first. We have delivered projects for clients in London, Dublin, Amsterdam, and two firms in the United States. On-site visits are arranged when the project scope warrants them.

What does a typical engagement cost?

Discovery runs between £2,500 and £5,000. A proof of concept sits in the £8,000 to £18,000 range depending on complexity. Full production builds vary widely; a straightforward predictive model might be £25,000 while a multi-modal computer vision system could reach six figures. We provide fixed-price quotes after discovery so there are no surprises.

Who owns the intellectual property?

You do. Every model, dataset derivative, and pipeline script we create during an engagement belongs to your company. We retain the right to reuse general methodologies and open-source tooling, but your proprietary data and trained weights are yours alone.

Can you integrate with our existing software?

We have built integrations for Salesforce, SAP, Dynamics 365, Shopify, custom ERPs, and a range of internal tools using REST and gRPC APIs. If your system exposes an interface, we can connect to it. If it does not, we discuss middleware options during scoping.

Tell us about the problem you want solved

Whether you have a clear brief or just a hunch that AI could help, we are happy to talk it through. The initial conversation is free and typically lasts 30 minutes.

Visit us:
344 North Lane, St. Wintheiser, Scotland, BS06 0PD, United Kingdom

Call:
+44 372 561 7082

Email:
[email protected]